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ChaosPixels: Collaborative Website Building Experiment

Hacker News

ChaosPixels: Collaborative Website Building Experiment

Hey HN, I've been wanting to start this project for a long time, ever since I read an article about collaborative transformation of blob images[1], and I'm hoping it will take off here as I'm curious to see how it can grow. Here's how it works: - My website is available at https://chaospixels.com . You can find its code in the `src` directory of the linked repository. - Every day, I'll review all the open PRs (Pull Requests) and calculate a PR score based on the number of thumbs-up on the PR's opening comment. - The PR with the highest score will be merged and deployed. - Afterward, I'll close all the other PRs, and we'll start fresh the next day. --- [1] There was an experiment involving collaborative manipulation of blob images. Unfortunately, I can no longer find it. Maybe some of you can help locate it.

Visit product View on Hacker NewsApr 11, 2024

Actual performance

5points

2comments

Did not reach leaderboard

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Product HuntOn track for Day 1 leaderboard · Strong signals: code, open · Missing: mac, agents, macos

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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